中文摘要：

针对混沌优化算法易陷入局部最优、收敛慢和精度低的缺点，提出一种改进的变尺度混合混沌优化算法。为保证算法的全局收敛性，采用具有更好遍历性的Kent混沌映射代替传统的Logistic混沌映射；为提高收敛速度和解的精度，引入新的变尺度因子，在搜索最优解的末期使用Nelder‐Mead单纯形法。通过数值实验对相关的4种算法进行比较，比较结果表明，该算法可以保证解的全局最优性、提高算法的收敛速度并提高获得的最优解精度。

英文摘要：

To achieve global optimality of optimal value ,fast convergence and high accuracy ,an improved hybrid scale chaos op‐timization algorithm based on Kent chaotic map was proposed ,which consisted of two stages .In the first stage ,Kent map was applied to generate initial chaotic variables instead of using Logistic map .In the second stage ,scale chaotic optimization per‐formed at the beginning and Nelder‐Mead simplex algorithm was applied for a more accurate solution at the end .The numerical results show that the proposed algorithm can ensure the global optimality of optimal value and improve the accuracy and efficiency of the algorithm .